VANETs安全应用性能综合评估与优化

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"用于安全相关应用的VANET的综合性能评估" 在车辆自组织网络（VANETs）中，广播通信作为一种关键的技术，被广泛用于传播安全相关的消息，以确保驾驶员能够及时接收到附近的危险警告和其他重要信息。然而，广播通信的特性，如多径衰落、干扰以及高动态性，往往会导致消息传输的可靠性降低。因此，对VANETs的安全相关应用进行综合性能评估显得至关重要。本研究提出了一种全面的评估方案，旨在优化VANETs的性能并保障服务质量。该方案分为三个主要部分： 1. 应用层次分析法（Analytic Hierarchy Process, AHP）：AHP是一种决策分析工具，用于处理复杂问题中的多准则决策。在这个评估方案中，AHP被用来根据用户对安全相关应用的优先级确定不同访问类别的相对权重。这一步骤有助于理解不同应用场景对网络性能的影响程度。 2. 综合熵和AHP：熵是一种衡量信息不确定性的度量，常用于评估系统的复杂性和多样性。通过结合熵与AHP，研究者可以更准确地量化性能指标的权重。这种方法可以帮助识别哪些性能指标对整体系统性能影响最大，从而针对性地优化网络设置。 3. 灰色关联度分析法（Grey Relation Analysis, GRA）：灰色关联度分析是一种比较不同方案之间相似程度的方法，它在不完全或模糊信息条件下尤其有用。在VANETs的场景中，GRA用于对各种可能的解决方案进行排序，找出最优的广播策略，以提高消息的传递效率和可靠性。通过这些步骤，研究人员能够分析VANETs在安全相关应用中的表现，包括消息的传播效率、接收率、时延等关键性能指标。分析结果表明，所提出的综合评估方案不仅能够有效地评估VANETs的性能，还能在考虑了各种功能和约束的情况下，为优化网络配置提供指导。此外，这项工作还强调了在VANETs环境中，考虑到用户需求和网络动态性的性能评估的重要性。通过这样的综合评估，可以更好地理解广播通信的局限性，从而设计出更适应实际路况的通信策略，提升VANETs的安全性和可靠性。这篇研究为VANETs的安全相关应用提供了科学的评估框架，为未来VANETs的优化设计和实际部署提供了理论依据和技术支持。

determines weights according to the preference of decision makers or experts, which is

volatile due to the unreliability judgment of decision makers. The representative methods

of subjective approaches are analytic hierarchy process (AHP) [14] and fuzzy MADM [15].

However, the fuzzy MADM methods require cumbersome computations, and they are not

suitable for solving problems with more than ten alternatives [16]. The objective ap-

proaches rely on the performance of the evaluation objects to determine the weight,

whereas, it does not consider the subjective idea of decision-makers. The representative

methods of objective approach are entropy [16] and principal component analysis (PCA).

While, PCA requires the meaning of the weights should be exclusive statistical and it also

may lead to information lost.

Consideration of the user preference, and restraining the subjectivity and arbitrariness,

the subjective and objective approaches should be combined. There are numbers of pub-

lications that combined two approaches together to determine the weights. Reference [17]

combined AHP with entropy to evaluate the safety of smart grid. In [18], the authors

proposed an improved fuzzy comprehensive evaluation method for assessing the perfor-

mance of leak detection systems, while the weights are calculated by combing entropy with

AHP. Reference [19] used the combined weight, i.e. AHP and entropy methods, to de-

termine the importance of the evaluation criteria. Reference [20] used AHP and entropy to

acquire attribute weights’ vectors, and then synthesized the weights’ vectors by using

group decision making.

After the weights have been determined, the alternatives (i.e. number of vehicles)

should be ranked before obtaining the optimal network performance of VANETs.

Several evaluation methods have been used for network selection to rank the alterna-

tives in heterogeneous wireless networks, such as technique for order preference by

similarity to ideal solution (TOPSIS) [21]. The authors developed weighted rating of

multiple attributes (WRMA) method to rate attribute, and TOPSIS was employed to rank

networks in Ref. [22]. However, Ref. [23] pointed out that grey relational analysis (GRA)

achieved better performance than TOPSIS for speciﬁc service type, i.e. interactive and

background. The author in [24] applied entropy and TOPSIS for network selection.

Due to the fact that in VANETs, the safety-related application that is selected by the

user is subjective and the network performance metrics are objective, we use a hybrid

approach, which combines AHP with entropy approaches, to evaluate the performance

comprehensively. Then, GRA [25] is used for ranking. And it has been used to provide a

simple and transparent evaluation procedure for a clear cut ranking order of strategies

derives in [26].

In this paper, a comprehensive evaluation scheme has been proposed to obtain the

optimal performance of VANET. The AHP and entropy approaches have been combined to

determine weights. The former determines the relative weights among different ACs ac-

cording to the user preference, i.e. safety-related applications. And the latter is used to

determine the weights of performance metrics, i.e. time delay, throughput and PDR. Then

the GRA has been adopted to rank the alternatives to achieve the highest resource uti-

lization of VANETs. To the authors’ knowledge, this is the ﬁrst time to determine the

weights among different ACs in VANETs, which takes the user preference into account.

The main contributions of this paper are summarized as follows: (1) a comprehensive

scheme is proposed for the performance evaluation of VANETs. (2) The proposed scheme

takes the user preference and the performance metrics into account. And it uses AHP and

entropy to calculate the weights. (3) The comprehensive evaluation results are ranked using

GRA to obtain the optimum network performance.

Comprehensive Performance Evaluation of VANETs for… 3019

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